Dynamic planning for urban drayage operations

This paper develops approaches for incorporating informational and operational dynamics within models for intermodal drayage operations with flexible tasks. Tasks with flexible origins or destinations create an important complexity. We develop models to minimize the cost of drayage moves when flexibility exists. The solution approach generates plans at several decision epochs during the day. The optimization problem at each epoch is a complex multistage stochastic optimization problem; we find good solutions using a two-stage approximation. We show that with such a model, a drayage firm can find high-quality plans even when many tasks are not known initially.

Research highlights
► We propose a dynamic approach to drayage routing with a two-stage stochastic optimization model.
► The approach uses detailed information for the near-term and approximations of future requests.
► The approach finds high-quality plans that outperform other rolling horizon approaches.
► The approach allows practitioners to evaluate the cost of making conservative planning decisions.